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Decadal prediction of sustainable agricultural
and forest management - Earth system
prediction differs from climate predic...
Decadal prediction of sustainable agricultural and forest management -
Earth system prediction differs from climate predic...
Carbon storage
Crop/forest yields
Model response
Parameter
uncertainty
Structural
uncertainty
Ecological uncertainty
Varia...
Crop
Management
in CESM
(NCAR)
Forest
management
in CESM
(Virginia Tech)
Management
alternatives
Key areas of
ecological
u...
Crop
Management
in CESM
(NCAR)
Forest
management
in CESM
(Virginia Tech)
Management
alternatives
Key areas of
ecological
u...
Chapin et al. 2008
(IPCC 2007)
Earth system models
Earth system models use mathematical
formulas to simulate the physical,
chemical, and biol...
Surface energy fluxes Hydrology Biogeochemistry
Landscape dynamics
The Community Land Model
Fluxes of energy, water,
CO2, ...
Surface energy fluxes Hydrology Biogeochemistry
Landscape dynamics
The Community Land Model
Fluxes of energy, water,
CO2, ...
Examples from project
• How can cover crops impact climate?
• What matters more for climate: species,
location, or intensi...
Examples from project
• How can cover crops impact climate?
- Increased LAI 0 from 4
outside of growing
season for all cro...
Key caveats:
• Results depend on height of cover crop
• Leaf Area Index an assumed value (4 m2 m-2)
• Greenhouse gases not...
Examples from project
• What matters more for climate: species,
location, or intensity of a forest management
project?
Led...
Examples from project
• What matters more for climate: species,
location, or intensity of a forest management
project?
Sta...
Establish pine trees (LAI = 4) on cropland
△℃
Summer
Surface
temperatures
Shift to broadleaf trees
Establish pine trees (LAI = 4) on cropland
△℃
Summer
Surface
temperatures
Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4)
Establish pine trees (LAI = 4) on cropland
△℃
Summer
...
Shift to broadleaf increased albedo Decreasing LAI increases albedo
Establishing pine trees on cropland decreases albedo
△...
Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4)
Establish pine trees (LAI = 4) on cropland
△℃
Summer
...
Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4)
Establish pine trees (LAI = 4) on cropland
△℃
Summer
...
Examples from project
• How does the acclimation of photosynthesis
and respiration to warming temperatures
influence clima...
Processrate
Leaf temperature (°C)
Cool grown
Warm grown
Hot grown
Response can shift with acclimation
Photosynthesis and l...
-90
<60°S
-1.0
-0.5
0.0
0.5
1.0
-90-4504590
<60°S
60°S-20°S
20°S-20°N
20°N-60°N
>60°N
1.0
4590
20°N-60°N
>60°N
Smith, NG e...
Acclimation increases photosynthesis,
but varies by plant type
0
50
100
150
200
Jmax(µmolm-2
s-1
)
C3 Annual (a)
Ta=15°C
T...
Carbon storage
Crop/forest yields
-1.0
-0.5
0.0
0.5
1.0
-90-4504
<60°S
60°S-20°S
20°S-20°N
20°N-60°N
MAM
*
*
-1.0
-0.5
0.0...
Decadal prediction of sustainable agricultural
and forest management - Earth system
prediction differs from climate predic...
Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate predic...
Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate predic...
Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate predic...
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Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction

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- Explore how crop and forest management influences decadal scale climate predictions
- Improve the representation of managed ecosystems in Earth system models
- Specific focus on institutional strengths: soil carbon dynamics, pine plantation forestry, plant physiology under warming temperatures, forest nitrogen cycling
- Evaluate and reduce uncertainty associated with ecological processes in climate predictions

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Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction

  1. 1. Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction R. Quinn Thomas (Virginia Tech) Gordon Bonan (NCAR) Christine Goodale (Cornell University) Jed Sparks (Cornell University) Jeffrey Dukes (Purdue University) Serita Frey (U of New Hampshire) Stewart Grandy (U of New Hampshire) Thomas Fox (Virginia Tech) Harold Burkhart (Virginia Tech) Danica Lombardozzi (NCAR) William Wieder (NCAR) Susan Cheng (Cornell) Nicholas Smith (Purdue, LBNL) Benjamin Ahlswede (Virginia Tech) Joshua Rady (Virginia Tech) Emily Kyker-Snowman (U of New Hampshire) USDA-NIFA Project 2015-67003-23485
  2. 2. Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction PD: Quinn Thomas, Virginia Tech Funded through interagency Decadal and Regional Climate Prediction Using Earth System Models (EaSM) Program USDA-NIFA Project 2015-67003-23485 Objectives Approach Impacts - Explore how crop and forest management influences decadal scale climate predictions - Improve the representation of managed ecosystems in Earth system models - Specific focus on institutional strengths: soil carbon dynamics, pine plantation forestry, plant physiology under warming temperatures, forest nitrogen cycling - Evaluate and reduce uncertainty associated with ecological processes in climate predictions - Integrated effort involving climate modelers, ecosystem scientists, plant physiologists, soil scientists, and foresters. - New field measurements and synthesis of existing datasets for parameterization and evaluation of an Earth system model - Development and application of the Community Earth System Model - Crop and forest management strategies that maximize climate benefits - Earth system modeling tool available to the community to predict crop and timber production in a changing environment - Capacity building through connecting and training scientists to work at the interface of managed ecosystems and climate sciences
  3. 3. Carbon storage Crop/forest yields Model response Parameter uncertainty Structural uncertainty Ecological uncertainty Variation in management implementation
  4. 4. Crop Management in CESM (NCAR) Forest management in CESM (Virginia Tech) Management alternatives Key areas of ecological uncertainty Nitrogen export (Cornell University) Soil microbial dynamics (U of New Hampshire) Plant acclimation to temperature (Purdue University) Natural variability simulations (NCAR) Model response simulations (Team) Scenario forcing simulations (NCAR) Earth system prediction
  5. 5. Crop Management in CESM (NCAR) Forest management in CESM (Virginia Tech) Management alternatives Key areas of ecological uncertainty Nitrogen export (Cornell University) Soil microbial dynamics (U of New Hampshire) Plant temperature acclimation (Purdue University) Natural variability simulations (NCAR) Model response simulations (Team) Scenario forcing simulations (NCAR) Earth system prediction
  6. 6. Chapin et al. 2008
  7. 7. (IPCC 2007) Earth system models Earth system models use mathematical formulas to simulate the physical, chemical, and biological processes that drive Earth’s atmosphere, hydrosphere, biosphere, and geosphere A typical Earth system model consists of coupled models of the atmosphere, ocean, sea ice, and land Land is represented by its ecosystems, watersheds, people, and socioeconomic drivers of environmental change The model provides a comprehensive understanding of the processes by which people and ecosystems feed back, adapt to, and mitigate global environmental change
  8. 8. Surface energy fluxes Hydrology Biogeochemistry Landscape dynamics The Community Land Model Fluxes of energy, water, CO2, CH4, BVOCs, and reactive N and the processes that control these fluxes in a changing environment Temporal scale  30-minute coupling with atmosphere  Seasonal-to-interannual (phenology)  Decadal-to-century (disturbance, land use, succession)  Paleoclimate (biogeography) Spatial scale 1.25° long.  0.9375° lat. ~100 km  100 km
  9. 9. Surface energy fluxes Hydrology Biogeochemistry Landscape dynamics The Community Land Model Fluxes of energy, water, CO2, CH4, BVOCs, and reactive N and the processes that control these fluxes in a changing environment Temporal scale  30-minute coupling with atmosphere  Seasonal-to-interannual (phenology)  Decadal-to-century (disturbance, land use, succession)  Paleoclimate (biogeography) Spatial scale 1.25° long.  0.9375° lat. ~100 km  100 km Large focus on development and evaluation of CLM 5.0 (an open access, community resource)
  10. 10. Examples from project • How can cover crops impact climate? • What matters more for climate: species, location, or intensity of a forest management project? • How does the acclimation of photosynthesis and respiration to warming temperatures influence climate? Focus on idealized simulations to explore sensitivity of temperature to these biogeophysical land surface processes
  11. 11. Examples from project • How can cover crops impact climate? - Increased LAI 0 from 4 outside of growing season for all crops - Focus on winter (December-January- February) responses Led by: Danica Lombardozzi (NCAR)
  12. 12. Key caveats: • Results depend on height of cover crop • Leaf Area Index an assumed value (4 m2 m-2) • Greenhouse gases not simulated
  13. 13. Examples from project • What matters more for climate: species, location, or intensity of a forest management project? Led by: Ben Ahlswede (Virginia Tech)
  14. 14. Examples from project • What matters more for climate: species, location, or intensity of a forest management project? Standardizes for LAI across tree types and location
  15. 15. Establish pine trees (LAI = 4) on cropland △℃ Summer Surface temperatures
  16. 16. Shift to broadleaf trees Establish pine trees (LAI = 4) on cropland △℃ Summer Surface temperatures
  17. 17. Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4) Establish pine trees (LAI = 4) on cropland △℃ Summer Surface temperatures
  18. 18. Shift to broadleaf increased albedo Decreasing LAI increases albedo Establishing pine trees on cropland decreases albedo △ Albedo Summer albedo
  19. 19. Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4) Establish pine trees (LAI = 4) on cropland △℃ Summer Surface temperatures
  20. 20. Shift to broadleaf trees Lower LAI (2) is cooler than higher LAI (4) Establish pine trees (LAI = 4) on cropland △℃ Summer Surface temperatures Key caveats: • Greenhouse gases not simulated • Assumes grid-cell is entirely the plant type • Shift from crop to trees, other studies shift from bare ground to trees
  21. 21. Examples from project • How does the acclimation of photosynthesis and respiration to warming temperatures influence climate? - Used experimental data to parameterize acclimation - Simulated climate with and without acclimation Led by: Nick Smith (Purdue, now LBNL)
  22. 22. Processrate Leaf temperature (°C) Cool grown Warm grown Hot grown Response can shift with acclimation Photosynthesis and leaf respiration Smith and Dukes (2013) Global Change Biology
  23. 23. -90 <60°S -1.0 -0.5 0.0 0.5 1.0 -90-4504590 <60°S 60°S-20°S 20°S-20°N 20°N-60°N >60°N 1.0 4590 20°N-60°N >60°N Smith, NG et al. (In Review) Acclimation – No Acclimation △℃ Acclimation Photosynthesis Transpiration (Latent heat flux) Surface temperatures
  24. 24. Acclimation increases photosynthesis, but varies by plant type 0 50 100 150 200 Jmax(µmolm-2 s-1 ) C3 Annual (a) Ta=15°C Ta=20°C Ta=25°C Ta=30°C Ta=35°C 0 10 20 30 40 50 60 70 C3 Perennial (b) 0 50 100 150 200 250 C4 Annual (c) 0 10 20 30 40 50 0 50 100 150 200 C4 Perennial (d) 0 10 20 30 40 50 0 50 100 150 200 Tropical (e) 15 20 25 30 35 0 50 100 150 200 250 (f)C3 Annual C3 Perennial C4 Annual C4 Perennial Tropical Leaf temperature (°C) Smith and Dukes (In Review)
  25. 25. Carbon storage Crop/forest yields -1.0 -0.5 0.0 0.5 1.0 -90-4504 <60°S 60°S-20°S 20°S-20°N 20°N-60°N MAM * * -1.0 -0.5 0.0 0.5 1.0 -90-4504590 <60°S 60°S-20°S 20°S-20°N 20°N-60°N >60°N JJA * * -1.0 -0.5 0.0 0.5 1.0 -90-4504590 -180 -90 0 90 180 <60°S 60°S-20°S 20°S-20°N 20°N-60°N >60°N -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 SON ∆SAT (°C) *
  26. 26. Decadal prediction of sustainable agricultural and forest management - Earth system prediction differs from climate prediction R. Quinn Thomas (Virginia Tech) Gordon Bonan (NCAR) Christine Goodale (Cornell University) Jed Sparks (Cornell University) Jeffrey Dukes (Purdue University) Serita Frey (U of New Hampshire) Stewart Grandy (U of New Hampshire) Thomas Fox (Virginia Tech) Harold Burkhart (Virginia Tech) Danica Lombardozzi (NCAR) William Wieder (NCAR) Susan Cheng (Cornell) Nicholas Smith (Purdue, LBNL) Benjamin Ahlswede (Virginia Tech) Joshua Rady (Virginia Tech) Emily Kyker-Snowman (U of New Hampshire) USDA-NIFA Project 2015-67003-23485

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